Massage audio sleep-aiding method and intelligent sleep-aiding pillow with massage audio function

Abstract

The invention belongs to the technical field of sleep-aiding pillows, and particularly relates to a massage audio sleep-aiding method and an intelligent sleep-aiding pillow with a massage audio function. In order to overcome the defect that an existing intelligent sleep-aiding pillow cannot establish a personalized mode according to user information to carry out personalized regulation and control on an air bag and audio, the invention adopts the following technical scheme: the massage audio sleep-aiding method comprises the following steps: constructing a sleep-aiding audio massage model; acquiring user data; preprocessing user data; generating a personalized massage audio mode according to the preprocessed user data and the sleep-aiding audio massage model; and collecting real-time physiological data of the user, and regulating and controlling massage and audio in the sleep cycle according to the real-time physiological data of the user and the personalized massage audio mode. According to the control method of the intelligent sleep-aiding pillow, the personalized massage audio mode is generated, massage and audio can be adjusted according to different sleep stages of the user, and the user is better helped to fall asleep.

Description

Technical Field

[0001] The invention belongs to the technical field of sleep-aiding pillows, and in particular relates to a massage audio sleep-aiding method and an intelligent sleep-aiding pillow with a massage audio function. Background Art

[0002] Smart sleep-aid pillows are generally composed of a massage unit, a control unit, and a data sensor collection unit. The control unit provides users with a more comfortable and relaxing sleeping environment by adjusting the hardness and inflation speed of the airbag, thereby improving the user's sleep quality. The data collection unit generally has the function of collecting basic vital signs information and sleeping posture data of the user. These basic data can provide parameter basis for the adjustment of airbag massage. The mainstream massage units on the market are generally realized by airbags. According to different structures and the effects achieved, they can be divided into: separate design airbags, U-shaped airbags, and wavy airbags.

[0003] However, the existing smart sleep-aid pillows still have some problems in actual use. First, the existing smart sleep-aid pillows often massage according to the massage relaxation program preset in the main controller. This fixed massage method may lead to a poor massage relaxation experience. Secondly, the existing airbags are often large airbags or strip airbags, which can only lift and massage large areas of the human body, and cannot accurately stimulate and relieve pressure on the acupuncture points of the head and neck, resulting in a poor user experience. Finally, although the existing sensor units can collect human vital signs and sleeping posture data, they cannot or do not effectively apply these data to the feedback end or data analysis, but simply and directly convert the changes in these data into adjustments to the hardness and speed of the airbags, which fails to meet users' expectations for the massage and relaxation effects of smart pillows.

[0004] In addition, existing smart sleeping pillows fail to combine airbag massage and sleeping audio. Summary of the invention

[0005] The present invention aims at the deficiency that the existing intelligent sleep-aiding pillow cannot establish a personalized mode according to user information to perform personalized regulation of airbags and audio, and provides a massage audio sleep-aiding method, which generates a personalized mode by collecting real-time human body vital sign status data, and regulates the fingertip airbags and sleep-aiding audio accordingly. Furthermore, the personalized mode is adjusted according to previous sleep data. The present invention also provides an intelligent sleep-aiding pillow.

[0006] To achieve the above object, the present invention adopts the following technical solution: a massage audio sleep aid method, the massage audio sleep aid method comprising:

[0007] Step S1, constructing a sleep-aiding audio massage model, wherein the sleep-aiding audio massage model establishes a correlation between user data and a massage audio pattern, wherein the user data includes pre-stored data and real-time physiological data;

[0008] Step S2, obtaining pre-stored data, the pre-stored data including at least one of height, weight, gender, age, user head and neck sensitivity, and audio preference;

[0009] Step S3, user data preprocessing;

[0010] Step S4, generating a personalized massage audio mode according to the preprocessed user data and the personalized model;

[0011] Step S5, collecting real-time physiological data, and regulating the massage and audio during the sleep cycle according to the real-time physiological data and the personalized massage audio mode.

[0012] The control method of the smart sleeping-aiding pillow of the present invention is as follows: a sleeping-aiding audio massage model is pre-stored in the smart sleeping-aiding pillow; pre-processed user data is input into the sleeping-aiding audio massage model to generate a personalized massage audio mode; the personalized massage audio mode can better meet the personalized requirements of the user; the massage and audio in the sleep cycle are regulated according to the user's real-time physiological data and the personalized massage audio mode; the massage and audio parameters can be adjusted according to the user's different sleeping stages to better help the user fall asleep.

[0013] As an improvement, in step S1, the sleep-aiding audio massage model is expressed as:

[0014] MOD={M_F,M_I,EXT}

[0015] Among them, M_F, M_I, and EXT correspond to the user's massage frequency, massage intensity, and sleep-aiding audio effect quantitative indicators respectively.

[0016] As an improvement, in step S1, the process of constructing the sleep-aiding audio massage model includes:

[0017] Step S11, combining the audio parameter quantization results and the classification quantization results to construct a sleep-aiding audio effect quantization formula, which is expressed as:

[0018] EXT=λ*AQI+(1-λ)*CI=F (S_E)

[0019] Among them, λ is the adjustment coefficient, which is used to balance the proportion of audio parameter AQI and audio classification index CI in the overall quantization.

[0020] S_E is the audio preference, which corresponds to the quantitative value of the user's emotions and personality, expressed as:

[0021]

[0022] Among them, E represents the division of people with different personalities. maxThose who are extremely cheerful prefer relaxing and pleasant sleep-inducing audio. min It means that extremely introverted and sensitive people prefer soft and soothing sleep-aiding audio.

[0023] F (S_E) Indicates that the sleep-aiding audio effect quantization value is determined according to the audio preference S_E, λ*AQI+(1-λ)*CI=F (S_E) Indicates that the audio classification index CI and the audio parameter AQI are determined according to the quantitative value S_E of the user's emotion and personality;

[0024] In step S11, the audio classification index CI is expressed as:

[0025] CI=w_{C_t}*C_t+w_{S_p}*S_p+w_{U_a}*U_a

[0026] Among them, C_t is the content type, and each type is assigned a specific score, ranging from small to large according to the rhythm size;

[0027] S_p is style preference, which is scored based on the user’s emotional psychology;

[0028] U_a is used to evaluate whether it is suitable for the current specific sleep-aiding scenario. For a single occasion, the U_a value is fixed;

[0029] w_{C_t}, w_{S_p}, w_{U_a} are weight coefficients;

[0030] In step S11, under each specific audio classification, a sleep-aiding audio parameter quantization formula is generated according to the frequency range F, loudness L, rhythm change R, and timbre T, which is expressed as:

[0031] AQI=w_F*F+w_L*L+w_R*R+w_T*T

[0032] Among them, F is the frequency range, L is the loudness, R is the rhythm change, and T is the timbre.

[0033] w_F, w_L, w_R, and w_T are weight coefficients, which are allocated according to the importance of each parameter to the sleep-aiding audio effect.

[0034] As an improvement, in step S1, the process of constructing the sleep-aiding audio massage model includes:

[0035] Step S12, quantifying the airbag massage intensity, the airbag massage intensity calculation formula is expressed as:

[0036] M_I=w_P*P+w_A*A+w{U_P}*U_P=Y (S_M)

[0037] Among them, P is the airbag pressure, A is the massage area, and U_P is the user's preference score for massage intensity.

[0038] w_P, w_A, w{U_P} are weight coefficients, which are allocated according to the importance of each factor to the massage intensity, and w_P+w_A+w{U_P}=1,

[0039] S_M represents the current user's head and neck sensitivity, and the quantification formula is:

[0040]

[0041] Among them, M represents the user's head and neck sensitivity, and the sensitivity from high to low is M max and M min , M max Indicates the maximum sensitivity of the setting. Compared with other users, a higher massage intensity can achieve the best massage effect. min Indicates the minimum sensitivity set. Compared with other users, a smaller massage force can achieve the best massage effect. (S_M) Indicates that the airbag massage intensity is determined according to the current user's head and neck sensitivity S_M, w_P*P+w_A*A+w{U_P}*U_P=Y (S_M) Indicates selecting a unique combination from the airbag massage intensity set according to the current user's head and neck sensitivity S_M;

[0042] Step S13, quantifying the airbag massage frequency, the airbag massage frequency calculation formula is expressed as:

[0043]

[0044] Where T is the cycle time of airbag inflation and deflation, M_S is the switching frequency of massage mode, and U_F is the user's preference score for massage frequency. is the weight coefficient, which is assigned according to the importance of each factor to the frequency of massage, and

[0045] X (S_M) It is a function of S_M, indicating that the airbag massage frequency is determined according to the current user's head and neck sensitivity S_M. Indicates that a unique combination is selected from the airbag massage frequency set according to the current user's head and neck sensitivity S_M.

[0046] As an improvement, in step S11, the sleep-aiding audio effect quantification formula is expressed as:

[0047] EXT=λ*AQI+(1-λ)*CI=F (S_E，RELEX)

[0048] F (S_E，RELEX)It is a function of S_E and RELEX, indicating that the quantitative value of the sleep-aiding audio effect is determined based on the audio preference S_E and the current sleep trend RELEX, λ*AQI+(1-λ)*CI=F (S_E，RELEX) Indicates that the audio classification index CI and the audio parameter AQI are determined according to the user's quantitative value S_E of emotion and personality and the current sleep trend RELEX;

[0049] In step S12, the airbag massage intensity calculation formula is expressed as:

[0050] M_I=w_P*P+w_A*A+w{U_P}*U_P=Y (S_M，RELEX)

[0051] Y (S_M，RELEX) It is a function of S_M and RELEX, indicating that the airbag massage intensity is determined according to the current user's head and neck sensitivity S_M and the current sleep trend RELEX, w_P*P+w_A*A+w{U_P}*U_P=Y (S_M，RELEX) Indicates selecting a unique combination from the airbag massage intensity set according to the current user's head and neck sensitivity S_M and current sleep trend RELEX;

[0052] In step S13, the airbag massage frequency calculation formula is expressed as:

[0053]

[0054] X (S_M，RELEX) It is a function of S_M and RELEX, indicating that the airbag massage frequency is determined based on the current user's head and neck sensitivity S_M and the current sleep trend RELEX. Indicates selecting a unique combination from the airbag massage frequency set according to the current user's head and neck sensitivity S_M and current sleep trend RELEX;

[0055] Step S5 also includes:

[0056] Step S51, judging the current sleep trend of the user through RMSSD, and adjusting the massage mode and / or sleep-aiding audio according to the current sleep trend of the user.

[0057] As an improvement, in step S1, the current sleep relaxation trend index RELEX is set cur =F (RMSSDcur) , which is positively correlated with RMSSD, divides the sleep trend into several stages, expressed as:

[0058] RELEX = {(RELEX n-1 ,RELEX n )|n≥1}

[0059] From wakefulness to deep sleep, RELEX gradually increases;

[0060] In step S51, the current sleep relaxation trend index RELEX is obtained by calculating RMSSD. cur , if RELEX cur >RELEX n , determine whether the user has entered a deeper sleep stage from a lighter sleep stage, and adjust the massage mode and sleep-aiding audio to correspond to the next stage;

[0061] If RELEX cur <RELEX n-1 , determine whether the user has entered a lighter sleep stage from a deeper sleep stage, and adjust the massage mode and sleep-aid audio to correspond to the previous stage.

[0062] As an improvement, in step S1, the sleep-aiding audio massage model is expressed as:

[0063] MOD={P_R,M_F,M_I,EXT}

[0064] Among them, P_R corresponds to the user's personalized positive feedback quantitative index;

[0065] The massage audio sleep-aiding method further comprises:

[0066] Step S6, determining whether to adjust the personalized massage audio mode according to the real-time physiological data of the previous sleep cycle.

[0067] As an improvement, in step S1, the process of constructing the sleep-aiding audio massage model includes:

[0068] Step S13, quantify the personalized positive feedback index of the system, and the personalized positive feedback quantification index is expressed as:

[0069] P_R=α*S_H+β*P_H+γ*C_S

[0070] Among them, S_H is the user's current sleep habit score,

[0071] P_H is the user's preference history score,

[0072] C_S is the user's current physiological status score,

[0073] α, β, and γ are weight coefficients, which are allocated according to the importance of each factor to personalized recommendation, and α+β+γ=1.

[0074] As an improvement, in step S3, user data preprocessing includes at least one of clearing abnormal data, removing duplicate data, integrating data from multiple data sources into an integral data set, and data weight processing; and / or,

[0075] In step S5, real-time physiological data of the user is collected by a non-contact sensor; and / or,

[0076] In step S6, the real-time physiological data, massage data and audio data of the sleep cycle are sent to the cloud server, and the cloud server sends a modification instruction to the smart sleep-aid pillow. The smart sleep-aid pillow adjusts the personalized massage audio mode, and then adjusts the massage and / or audio settings during the sleep cycle.

[0077] A smart sleep-aiding pillow with a massage audio function, using the aforementioned massage audio sleep-aiding method, the smart sleep-aiding pillow comprises:

[0078] The main body of the smart sleep-aiding pillow includes a sleep-aiding pillow core base, a sleep-aiding pillow core, a fingertip airbag, a sleep-aiding audio module unit and a signal acquisition unit;

[0079] Air pressure source;

[0080] A control unit receives the signal sent by the signal acquisition unit and controls the air pressure source and the sleep-aiding audio module unit;

[0081] The integrated air-electric connection unit connects the air pressure source and the fingertip airbags, and connects the control unit and the sleep-aid audio module unit.

[0082] The beneficial effects of the control method of the intelligent sleep-aiding pillow of the present invention are as follows: a sleep-aiding audio massage model is pre-stored in the intelligent sleep-aiding pillow, and the pre-processed user data is input into the sleep-aiding audio massage model to generate a personalized massage audio mode, and the personalized massage audio mode can better meet the personalized requirements of the user; the massage and audio in the sleep cycle are regulated according to the user's real-time physiological data and the personalized massage audio mode, and the massage and audio can be adjusted according to the different sleep stages of the user to better help the user fall asleep. Furthermore, RMSSD is calculated, and the user's current sleep trend is judged according to the RMSSD, and the massage mode and / or sleep-aiding audio are adjusted according to the user's current sleep trend; whether to adjust the personalized massage audio mode is determined based on the real-time physiological data of the previous sleep cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is a flow chart of a control method of an intelligent sleep-aiding pillow according to a first embodiment of the present invention.

[0084] Figure 2 It is a more complete flow chart of the control method of the smart sleep-aiding pillow according to the first embodiment of the present invention.

[0085] Figure 3 It is a structural schematic diagram of the smart sleep-aiding pillow according to the first embodiment of the present invention.

[0086] Figure 4 It is a structural exploded view of the smart sleep-aiding pillow according to the first embodiment of the present invention.

[0087] In the figure, 1. main body of the smart sleep-aiding pillow; 11. base of the sleep-aiding pillow core; 12. cover of the sleep-aiding pillow; 13. fingertip airbag; 14. sleep-aiding audio module unit; 15. neck support stretching airbag;

[0088] 2. Control box;

[0089] 3. Integrated gas and electricity connection unit. DETAILED DESCRIPTION

[0090] The technical solutions of the embodiments of the present invention are explained and described below, but the following embodiments are only preferred embodiments of the present invention, not all. Based on the embodiments in the implementation mode, other embodiments obtained by those skilled in the art without creative work are all within the protection scope of the present invention.

[0091] See also Figures 1 to 3 , a massage audio sleep aid method according to an embodiment of the present invention, the massage audio sleep aid method comprising:

[0092] Step S1, constructing a sleep-aiding audio massage model, wherein the sleep-aiding audio massage model establishes a correlation between user data and a massage audio pattern, wherein the user data includes pre-stored data and real-time physiological data;

[0093] Step S2, obtaining pre-stored data, the pre-stored data including at least one of height, weight, gender, age, user head and neck sensitivity, and audio preference;

[0094] Step S3, user data preprocessing;

[0095] Step S4, generating a personalized massage audio mode according to the preprocessed user data and the personalized model;

[0096] Step S5, collecting real-time physiological data, and regulating the massage and audio during the sleep cycle according to the real-time physiological data and the personalized massage audio mode.

[0097] The control method of the intelligent sleep-aiding pillow of the present invention is that a sleep-aiding audio massage model is pre-stored in the intelligent sleep-aiding pillow, and pre-processed user data is input into the sleep-aiding audio massage model to generate a personalized massage audio mode, and the personalized massage audio mode can better meet the personalized requirements of the user; massage and audio in the sleep cycle are regulated according to the user's real-time physiological data and the personalized massage audio mode, and massage and audio can be adjusted according to the user's different sleeping stages to better help the user fall asleep. The user's real-time physiological data can also be pre-processed.

[0098] Embodiment 1

[0099] See also Figures 1 to 3, a massage audio sleep aid method according to a first embodiment of the present invention, the massage audio sleep aid method comprising:

[0100] Step S1, constructing a sleep-aiding audio massage model, wherein the sleep-aiding audio massage model establishes a correlation between user data and a massage audio pattern, wherein the user data includes pre-stored data and real-time physiological data;

[0101] Step S2, obtaining pre-stored data, the pre-stored data including at least one of height, weight, gender, age, user head and neck sensitivity, and audio preference;

[0102] Step S3, user data preprocessing;

[0103] Step S4, generating a personalized massage audio mode according to the preprocessed user data and the personalized model;

[0104] Step S5, collecting real-time physiological data, and regulating the massage and audio during the sleep cycle according to the real-time physiological data and the personalized massage audio mode.

[0105] In this embodiment, in step S1, the sleep-aiding audio massage model is represented as:

[0106] MOD={M_F,M_I,EXT}

[0107] Among them, M_F, M_I, and EXT correspond to the user's massage frequency, massage intensity, and sleep-aiding audio effect quantitative indicators respectively.

[0108] In this embodiment, in step S1, the process of constructing the sleep-aiding audio massage model includes:

[0109] Step S11, combining the audio parameter quantization results and the classification quantization results to construct a sleep-aiding audio effect quantization formula, which is expressed as:

[0110] EXT=λ*AQI+(1-λ)*CI=F (S_E)

[0111] Among them, λ is the adjustment coefficient, which is used to balance the proportion of audio parameter AQI and audio classification index CI in the overall quantization.

[0112] S_E is the audio preference, which corresponds to the quantitative value of the user's emotions and personality, expressed as:

[0113]

[0114] Among them, E represents the classification of people with different personalities, from outgoing to introverted. max and E min , E maxThose who are extremely cheerful prefer relaxing and pleasant sleep-inducing audio. min It means that extremely introverted and sensitive people prefer soft and soothing sleep-aiding audio.

[0115] F (S_E) It is a function of S_E, indicating that the quantitative value of the sleep-aiding audio effect is determined according to the audio preference S_E, λ*AQI+(1-λ)*CI=F (S_E) Indicates that the audio classification index CI and the audio parameter AQI are determined according to the quantitative value S_E of the user's emotion and personality;

[0116] In step S11, the audio classification index CI is expressed as:

[0117] CI=w_{C_t}*C_t+w_{S_p}*S_p+w_{U_a}*U_a

[0118] Among them, C_t is the content type, each type is assigned a specific score, ranging from small to large according to the rhythm size;

[0119] S_p is style preference, which is scored based on the user’s emotional psychology;

[0120] U_a is used to evaluate whether it is suitable for the current specific sleep-aiding scenario. For a single occasion, the U_a value is fixed;

[0121] w_{C_t}, w_{S_p}, w_{U_a} are weight coefficients;

[0122] In step S11, under each specific audio classification, a sleep-aiding audio parameter quantization formula is generated according to the frequency range F, loudness L, rhythm change R, and timbre T, which is expressed as:

[0123] AQI=w_F*F+w_L*L+w_R*R+w_T*T

[0124] Among them, F is the frequency range, L is the loudness, R is the rhythm change, and T is the timbre.

[0125] w_F, w_L, w_R, and w_T are weight coefficients, which are allocated according to the importance of each parameter to the sleep-aiding audio effect.

[0126] According to the differences in characteristics, rhythm and audio effects of sleep-aiding audio, it can be divided into white noise, natural environment sound, human voice guidance, ASMR (Autonomous Sensory Meridian Response) audio and sleep-aiding music. The characteristics of white noise, sleep-aiding music and ASMR audio are uniform distribution of frequency component power, steady and gentle rhythm, moderate audio volume, low variability and emotion, repetitiveness, and help relaxation and falling asleep. The rhythm of natural environment sound changes with nature, the spectrum varies according to the specific content environment, and the audio volume is adjusted according to the actual effect to achieve a relaxing effect. The rhythm of human voice-guided music is often designed to be close to the human heart rate, usually between 60 and 80 beats per minute. Such a rhythm can induce synergistic resonance with the internal cell tissue of the human body, helping the brain to enter a deep sleep state.

[0127] According to the emotional and psychological differences of different users, sleep-aiding audio can be classified and quantified according to the content, style and purpose of the audio. Therefore, an audio classification index CI is introduced. For different users and different sleep relaxation trends, there is a unique CI corresponding to each.

[0128] In this embodiment, in step S1, the process of constructing the sleep-aiding audio massage model includes:

[0129] Step S12, quantifying the airbag massage intensity, the airbag massage intensity calculation formula is expressed as:

[0130] M_I=w_P*P+w_A*A+w{U_P}*U_P=Y (S_M)

[0131] Among them, P is the airbag pressure, A is the massage area, and U_P is the user's preference score for massage intensity.

[0132] w_P, w_A, w{U_P} are weight coefficients, which are allocated according to the importance of each factor to the massage intensity, and w_P+w_A+w{U_P}=1,

[0133] S_M represents the current user's head and neck sensitivity, and the quantification formula is:

[0134]

[0135] Where M represents the user's head and neck sensitivity, M max Indicates the maximum sensitivity of the setting. Compared with other users, a higher massage intensity can achieve the best massage effect. min Indicates the minimum sensitivity set. Compared with other users, a smaller massage force can achieve the best massage effect.

[0136] Y (S_M)It is a function of S_M, indicating that the airbag massage intensity is determined according to the current user's head and neck sensitivity S_M, w_P*P+w_A*A+w{U_P}*U_P=Y (S_M) Indicates that a unique combination is selected from the airbag massage intensity set according to the current user's head and neck sensitivity S_M, namely, the airbag pressure P, the massage area A, and the user's preference score for massage intensity U_P;

[0137] Step S13, quantifying the airbag massage frequency, the airbag massage frequency calculation formula is expressed as:

[0138]

[0139] Where T is the cycle time of airbag inflation and deflation, M_S is the switching frequency of massage mode, and U_F is the user's preference score for massage frequency. is the weight coefficient, which is assigned according to the importance of each factor to the frequency of massage, and

[0140] X (S_M) It is a function of S_M, indicating that the airbag massage frequency is determined according to the current user's head and neck sensitivity S_M. It indicates that a unique combination is selected from the airbag massage frequency set according to the current user's head and neck sensitivity S_M, namely, the airbag inflation and deflation cycle time T, the massage mode switching frequency M_S and the user's preference score U_F for massage frequency.

[0141] In this embodiment, in step S11, the sleep-aiding audio effect quantification formula is expressed as:

[0142] EXT=λ*AQI+(1-λ)*CI=F (S_E，RELEX)

[0143] F (S_E，RELEX) It is a function of S_E and RELEX, indicating that the quantitative value of the sleep-aiding audio effect is determined based on the audio preference S_E and the current sleep trend RELEX, λ*AQI+(1-λ)*CI=F (S_E，RELEX) Indicates that the audio classification index CI and the audio parameter AQI are determined according to the user's quantitative value S_E of emotion and personality and the current sleep trend RELEX;

[0144] In step S12, the airbag massage intensity calculation formula is expressed as:

[0145] M_I=w_P*P+w_A*A+w{U_P}*U_P=Y (S_M，RELEX)

[0146] Y (S_M，RELEX)It is a function of S_M and RELEX, indicating that the airbag massage intensity is determined according to the current user's head and neck sensitivity S_M and the current sleep trend RELEX, w_P*P+w_A*A+w{U_P}*U_P=Y (S_M，RELEX) Indicates that a unique combination is selected from the airbag massage intensity set according to the current user's head and neck sensitivity S_M and current sleep trend RELEX, namely, the airbag pressure P, the massage area A, and the user's preference score for massage intensity U_P;

[0147] In step S13, the airbag massage frequency calculation formula is expressed as:

[0148]

[0149] X (S_M，RELEX) It is a function of S_M and RELEX, indicating that the airbag massage frequency is determined based on the current user's head and neck sensitivity S_M and the current sleep trend RELEX. Indicates that a unique combination is selected from the airbag massage frequency set according to the current user's head and neck sensitivity S_M and the current sleep trend RELEX, namely, the airbag inflation and deflation cycle time T, the massage mode switching frequency M_S and the user's preference score for massage frequency U_F;

[0150] Step S5 also includes:

[0151] Step S51, judging the current sleep trend of the user through RMSSD, and adjusting the massage mode and / or sleep-aiding audio according to the current sleep trend of the user.

[0152] The user's current sleep trend can be judged by RMSSD (Root Mean Square of Successive Differences). During sleep, changes in autonomic nervous system activity may cause changes in HRV (Heart Rate Variability) and RMSSD values. For example, in deep sleep, parasympathetic nerve activity is enhanced, HRV is usually higher, and RMSSD values ​​are also higher; while in light sleep or wakefulness, sympathetic nerve activity is enhanced, HRV is reduced, and RMSSD values ​​are also lower.

[0153] The calculation steps of RMSSD are as follows:

[0154] 1. Collect heart rate interval data: Collect continuous heart rate interval data within the current period, RR = {RR0, RR1, ..., RR n}.

[0155] 2. Calculate the difference: DIFF = {RR1-RR0,RR2-RR1,...,RR n -RRn-1}.

[0156] 3. Find the sum of squares:

[0157] 4. Calculate the RMS:

[0158] For example, given the heart beat interval data: 1000, 1020, 980, 1010, 990, 1000, 970, 1030, 990, 1000, calculate the RMSSD:

[0159] 1. Calculate the difference between adjacent heart beat intervals:

[0160] ΔRR0=1020-1000=20

[0161] ΔRR1=980-1020=-40 ...

[0163] ΔRR n =1000-990=10

[0164] 2. Calculate the squares of these differences:

[0165] (ΔRR0) 2 =400

[0166] (ΔRR1) 2 =1600 ...

[0168] (ΔRR n ) 2 =100

[0169] 3. Find the sum of these square values:

[0170] 400+1600+...+100=6400

[0171] 4. Calculate the mean square error:

[0172]

[0173] In this embodiment, in step S1, the current sleep relaxation trend index RELEX is set cur =F (RMSSDcur) , which is positively correlated with RMSSD, divides the sleep trend into several stages, expressed as:

[0174] RELEX = {(RELEX n-1 ,RELEX n )|n≥1}

[0175] From wakefulness to deep sleep, RELEX gradually increases;

[0176] In step S51, the current sleep relaxation trend index RELEX is obtained by calculating RMSSD. cur , if RELEX cur >RELEX n , determine whether the user has entered a deeper sleep stage from a lighter sleep stage, and adjust the massage mode and sleep-aiding audio to correspond to the next stage;

[0177] If RELEX cur <RELEX n-1 , determine whether the user has entered a lighter sleep stage from a deeper sleep stage, and adjust the massage mode and sleep-aid audio to correspond to the previous stage.

[0178] Corresponding to different sleep stages, the massage modes and sleep-aid audio are different. For example, from light sleep to deep sleep, the massage intensity, massage frequency, and audio loudness gradually decrease.

[0179] In this embodiment, in step S1, the sleep-aiding audio massage model is represented as:

[0180] MOD={P_R,M_F,M_I,EXT}

[0181] Among them, P_R corresponds to the user's personalized positive feedback quantitative index;

[0182] The massage audio sleep-aiding method further comprises:

[0183] Step S6, determining whether to adjust the personalized massage audio mode according to the real-time physiological data of the previous sleep cycle.

[0184] In this embodiment, in step S1, the process of constructing the sleep-aiding audio massage model includes:

[0185] Step S13, quantify the personalized positive feedback index of the system, and the personalized positive feedback quantification index is expressed as:

[0186] P_R=α*S_H+β*P_H+γ*C_S

[0187] Among them, S_H is the user's current sleep habit score,

[0188] P_H is the user's preference history score,

[0189] C_S is the user's current physiological status score,

[0190] α, β, and γ are weight coefficients, which are allocated according to the importance of each factor to personalized recommendation, and α+β+γ=1.

[0191] In this embodiment, in step S3, user data preprocessing includes at least one of clearing abnormal data, removing duplicate data, integrating data from multiple data sources into an overall data set, and data weight processing.

[0192] In this embodiment, in step S5, the real-time physiological data of the user is collected by a non-contact sensor.

[0193] In this embodiment, in step S6, the real-time physiological data, massage data and audio data of the sleep cycle are sent to the cloud server, and the cloud server sends a modification instruction to the smart sleep-aid pillow. The smart sleep-aid pillow adjusts the personalized massage audio mode, and then adjusts the massage and / or audio settings during the sleep cycle.

[0194] After a sleep-aiding cycle (usually the first sleep process of a night) is completed, the smart sleep-aiding pillow will send the recorded user's physical signs, sleep trends and other status information to the cloud server through the wireless communication module. The cloud server allocates a separate storage unit for each user to record the user's historical status data. Cloud storage enables centralized data management, simplifies the access process, improves efficiency, and assists in accurate decision-making. Based on cloud algorithms, personalized sleep improvement suggestions can be generated for users.

[0195] The cloud server also decides whether to adjust the parameters in the personalized model based on the user's vital signs, sleep trends and other status information received.

[0196] See also Figure 3 and Figure 4 In this embodiment, the smart sleeping pillow includes:

[0197] The main body 1 of the smart sleep-aiding pillow includes a sleep-aiding pillow core base 11, a sleep-aiding pillow cover 12, a fingertip airbag 13, a sleep-aiding audio module unit 14 and a signal acquisition unit;

[0198] Air pressure source;

[0199] A control unit receives signals from the signal acquisition unit and controls the air pressure source and the sleep-aiding audio module unit 14;

[0200] The integrated air-electric connection unit 3 is connected to the air pressure source and the fingertip airbag 13 , and is connected to the control unit and the sleep-aiding audio module unit 14 .

[0201] In this embodiment, the smart sleeping-aiding pillow body 1 further includes a neck supporting and stretching airbag 15 .

[0202] In this embodiment, the smart sleeping-aiding pillow includes a control box 2 , in which an air pressure source and a control unit are disposed.

[0203] In this embodiment, the signal acquisition unit is used to collect real-time physiological data of the user, and the real-time physiological data includes heart rate, breathing rate, etc.

[0204] In this embodiment, the control box 2 is not provided with an interactive interface, but is interacted with through a mobile phone, a tablet, etc. The user inputs relevant data through software installed on the mobile phone, the tablet, etc. The control box 2 stores relevant running programs to control the airbag and the sleep-aiding audio module unit 14.

[0205] In this embodiment, the integrated gas-electric connection unit 3 contains two gas pipe pathways and two electrical pathways, which provide signal pathways for airbag inflation and deflation and sleep-aid audio modules.

[0206] In this embodiment, the sleep-aiding pillow cover 12 wraps the sleep-aiding pillow core base 11, and the sleep-aiding pillow core base 11 includes an upper layer and a lower layer, both of which use memory foam pillow cores, and the density of the lower layer is higher than that of the upper layer, so that the lower layer provides basic pressure support for the upper layer, creating a comfortable sleeping microenvironment for the user, and helping to improve sleep quality. The lower layer can automatically adjust according to the shape of the head and neck, provide personalized support for the neck, maintain the natural curve of the cervical spine, reduce the pressure caused by the weight of the head, and provide a more comfortable sleeping experience for the user.

[0207] In this embodiment, the sleep-aiding audio module unit 14 includes two sets of stereo speaker components.

[0208] In this embodiment, the airbag, the sleep-aiding audio module unit 14 and the signal acquisition unit are all located in the sleep-aiding pillow cover 12 and in the sleep-aiding pillow core base 11 .

[0209] In this embodiment, the smart sleep-aiding pillow has a wireless communication module for communicating with a cloud server. Usually, the wireless communication module is wifi.

[0210] In this embodiment, the smart sleep-aid pillow is pre-stored with a sleep-aid audio and massage personalized model (program). When using it for the first time, the user usually needs to log in and enter basic information such as height, weight, gender, and age. The user's head and neck sensitivity, massage softness and hardness preferences, and emotional personality and other sensory and psychological information are obtained through questions and answers or experience (for example, asking the user whether the current intensity and frequency of a certain massage intensity and massage frequency are appropriate). When constructing the sleep-aid audio and massage personalized model before leaving the factory, the required relevant data is obtained through questionnaires and other methods.

[0211] In this embodiment, the program pre-stored in the smart sleep-aiding pillow may also include several typical population settings for users to refer to and modify on this basis.

[0212] The solution of this embodiment is described in more detail below.

[0213] The fingertip airbags of the smart sleep-aid pillow (not considering the neck support and stretching airbags) can provide three levels of massage intensity and three levels of massage frequency. There are three types of audio in the sleep-aid audio module unit (with different audio classification indexes CI), and each of the three types of audio has three audios (with different audio parameters AQI).

[0214] When using for the first time, after logging in, the user enters personal information such as height, weight, gender, age, etc., and obtains the user's head and neck sensitivity, massage soft and hard preferences, and audio preferences through questionnaires and / or actual experience (you can also skip and directly select a pre-stored reference mode). After obtaining part or all of the required user data, data preprocessing is performed (clearing abnormal data, etc.), and the first massage audio mode of the current user is generated, with massage intensity and massage frequency both in the middle range, and audio with an AQI of the middle value under the CI of the middle value (referred to as middle audio).

[0215] In the first massage audio mode, the personalized model of the smart sleep pillow adjusts the massage intensity, frequency and audio according to the user's real-time physiological data, including judging the user's sleep trend according to RMSSD, judging the sleep stage according to the user's sleep trend and adjusting the massage and audio accordingly. For example, the sleep stage is divided into awake, light sleep, and semi-deep sleep, and the medium-range massage intensity and medium-range massage frequency are further divided into three small stages according to the stage, and the audio loudness is also divided into three small ranges.

[0216] Usually, the first massage audio mode is only run during the first sleep process of the user at night. The real-time physiological data of the user can be collected during the whole sleep process. Of course, the first massage audio mode can also be run during multiple sleep processes (if any) throughout the night.

[0217] After the first night of use, the user can choose to upload the first night's sleep data to the cloud server, which will determine the user's sleep quality, issue sleep suggestions and / or ask the user whether to optimize the mode (it can also be set to automatic optimization). Of course, for privacy or other reasons, the user can also choose not to upload the data to the cloud server. At this time, the user can modify and adjust the parameters in the local settings.

[0218] When the user manually accepts the optimization or sets the automatic optimization, the cloud server sends a change instruction to the smart sleep-aiding pillow, and the smart sleep-aiding pillow modifies the settings in the first massage audio mode, or adds a second massage audio mode. In the subsequent sleep process, the first massage audio mode or the second massage audio mode is used.

[0219] After logging in, the user can create multiple users, and each user can set multiple time or other modes (such as nap mode, night mode, afternoon mode, etc.). When the user has not yet determined a satisfactory mode, multiple modes can be stored in a single time mode for the user to compare and choose. For example, different night modes 1, night mode 2, and night mode 3 are generated for three consecutive nights. The best experience is selected from the three night modes as the default night mode, and the other two are deleted (or retained).

[0220] The above is only a specific implementation of the invention, but the protection scope of the invention is not limited thereto. Those skilled in the art should understand that the invention includes but is not limited to the contents described in the above specific implementation. Any modification that does not deviate from the functional and structural principles of the invention will be included in the scope of the claims.

Claims

1. A massage audio sleep aid method, characterized in that: The massage audio sleep-aiding method comprises: Step S1, constructing a sleep-aiding audio massage model, wherein the sleep-aiding audio massage model establishes a correlation between user data and a massage audio pattern, wherein the user data includes pre-stored data and real-time physiological data; Step S2, obtaining pre-stored data, the pre-stored data including at least one of height, weight, gender, age, user head and neck sensitivity, and audio preference; Step S3, user data preprocessing; Step S4, generating a personalized massage audio mode according to the preprocessed user data and the personalized model; Step S5, collecting real-time physiological data, and regulating the massage and audio during the sleep cycle according to the real-time physiological data and the personalized massage audio mode.

2. The method for aiding sleep with massage audio according to claim 1, characterized in that: In step S1, the sleep-aiding audio massage model is expressed as: MOD={M_F,M_I,EXT} Among them, M_F, M_I, and EXT correspond to the user's massage frequency, massage intensity, and sleep-aiding audio effect quantitative indicators respectively.

3. The method of massage audio to aid sleep according to claim 2, characterized in that: In step S1, the process of constructing the sleep-aiding audio massage model includes: Step S11, combining the audio parameter quantization results and the classification quantization results to construct a sleep-aiding audio effect quantization formula, which is expressed as: EXT=λ*AQI+(1-λ)*CI=F (S_E) Among them, λ is the adjustment coefficient, which is used to balance the proportion of audio parameter AQI and audio classification index CI in the overall quantization. S_E is the audio preference, which corresponds to the quantitative value of the user's emotions and personality, expressed as: Among them, E represents the classification of people with different personalities, from outgoing to introverted. max and E min , E max Those who are extremely cheerful prefer relaxing and pleasant sleep-inducing audio. min It means that extremely introverted and sensitive people prefer soft and soothing sleep-aiding audio. F (S_E) Indicates that the sleep-aiding audio effect quantization value is determined according to the audio preference S_E, λ*AQI+(1-λ)*CI=F (S_E) Indicates that the audio classification index CI and the audio parameter AQI are determined according to the quantitative value S_E of the user's emotion and personality; In step S11, the audio classification index CI is expressed as: CI=w_{C_t}*C_t+w_{S_p}*S_p+w_{U_a}*U_a Among them, C_t is the content type, each type is assigned a specific score, ranging from small to large according to the rhythm size; S_p is style preference, which is scored based on the user’s emotional psychology; U_a is used to evaluate whether it is suitable for the current specific sleep-aiding scenario. For a single occasion, the U_a value is fixed; w_{C_t}, w_{S_p}, w_{U_a} are weight coefficients; In step S11, under each specific audio classification, a sleep-aiding audio parameter quantization formula is generated according to the frequency range F, loudness L, rhythm change R, and timbre T, which is expressed as: AQI=w_F*F+w_L*L+w_R*R+w_T*T Among them, F is the frequency range, L is the loudness, R is the rhythm change, and T is the timbre. w_F, w_L, w_R, and w_T are weight coefficients, which are allocated according to the importance of each parameter to the sleep-aiding audio effect.

4. The method for aiding sleep with massage audio according to claim 2, characterized in that: In step S1, the process of constructing the sleep-aiding audio massage model includes: Step S12, quantifying the airbag massage intensity, the airbag massage intensity calculation formula is expressed as: M_I=w_P*P+w_A*A+w{U_P}*U_P=Y (S_M) Among them, P is the airbag pressure, A is the massage area, and U_P is the user's preference score for massage intensity. w_P, w_A, w{U_P} are weight coefficients, which are allocated according to the importance of each factor to the massage intensity, and w_P+w_A+w{U_P}=1, S_M represents the current user's head and neck sensitivity, and the quantification formula is: Among them, M represents the user's head and neck sensitivity, and the sensitivity from high to low is M max and M min , M max Indicates the maximum sensitivity of the setting. Compared with other users, a higher massage intensity can achieve the best massage effect. min Indicates the minimum sensitivity set. Compared with other users, a smaller massage force can achieve the best massage effect. Y (S_M) Indicates that the airbag massage intensity is determined according to the current user's head and neck sensitivity S_M, w_P*P+w_A*A+w{U_P}*U_P=Y (S_M) Indicates selecting a unique combination from the airbag massage intensity set according to the current user's head and neck sensitivity S_M; Step S13, quantifying the airbag massage frequency, the airbag massage frequency calculation formula is expressed as: Among them, T is the cycle time of airbag inflation and deflation, M_S is the switching frequency of massage mode, U_F is the user's preference score for massage frequency, δ, φ is the weight coefficient, which is assigned according to the importance of each factor to the frequency of massage, and X (S_M) It is a function of S_M, indicating that the airbag massage frequency is determined according to the current user's head and neck sensitivity S_M. Indicates selecting a unique combination from the airbag massage frequency set according to the current user's head and neck sensitivity S_M.

5. The method of massage audio to aid sleep according to claim 2, characterized in that: In step S11, the sleep-aiding audio effect quantification formula is expressed as: EXT=λ*AQI+(1-λ)*CI=F (S_E，RELEX) F (S_E，RELEX) It is a function of S_E and RELEX, indicating that the quantitative value of the sleep-aiding audio effect is determined based on the audio preference S_E and the current sleep trend RELEX, λ*AQI+(1-λ)*CI=F (S_E，RELEX) Indicates that the audio classification index CI and the audio parameter AQI are determined according to the user's quantitative value S_E of emotion and personality and the current sleep trend RELEX; In step S12, the airbag massage intensity calculation formula is expressed as: M_I=w_P*P+w_A*A+w{U_P}*U_P=Y (S_M，RELEX) Y (S_M，RELEX) It is a function of S_M and RELEX, indicating that the airbag massage intensity is determined according to the current user's head and neck sensitivity S_M and the current sleep trend RELEX, w_P*P+w_A*A+w{U_P}*U_P=Y (S_M，RELEX) Indicates selecting a unique combination from the airbag massage intensity set according to the current user's head and neck sensitivity S_M and current sleep trend RELEX; In step S13, the airbag massage frequency calculation formula is expressed as: X (S_M，RELEX) It is a function of S_M and RELEX, indicating that the airbag massage frequency is determined based on the current user's head and neck sensitivity S_M and the current sleep trend RELEX. Indicates selecting a unique combination from the airbag massage frequency set according to the current user's head and neck sensitivity S_M and current sleep trend RELEX; Step S5 also includes: Step S51, judging the current sleep trend of the user through RMSSD, and adjusting the massage mode and / or sleep-aiding audio according to the current sleep trend of the user.

6. The method for aiding sleep with massage audio according to claim 5, characterized in that: In step S1, the current sleep relaxation trend index RELEX is set cur =F (RMSSDcur) , which is positively correlated with RMSSD, divides the sleep trend into several stages, expressed as: RELEX={(RELEX n-1 ,RELEX n )|n≥1} From wakefulness to deep sleep, RELEX gradually increases; In step S51, the current sleep relaxation trend index RELEX is obtained by calculating RMSSD. cur , if RELEX cur >RELEX n , determine whether the user has entered a deeper sleep stage from a lighter sleep stage, and adjust the massage mode and sleep-aiding audio to correspond to the next stage; If RELEX cur <RELEX n-1 , determine whether the user has entered a lighter sleep stage from a deeper sleep stage, and adjust the massage mode and sleep-aid audio to correspond to the previous stage.

7. The method for aiding sleep with massage audio according to claim 2, characterized in that: In step S1, the sleep-aiding audio massage model is expressed as: MOD={P_R,M_F,M_I,EXT} Among them, P_R corresponds to the user's personalized positive feedback quantitative index; The massage audio sleep-aiding method further comprises: Step S6, determining whether to adjust the personalized massage audio mode according to the real-time physiological data of the previous sleep cycle.

8. The method for aiding sleep with massage audio according to claim 7, characterized in that: In step S1, the process of constructing the sleep-aiding audio massage model includes: Step S13, quantify the personalized positive feedback index of the system, and the personalized positive feedback quantification index is expressed as: P_R=α*S_H+β*P_H+γ*C_S Among them, S_H is the user's current sleep habit score, P_H is the user's preference history score, C_S is the user's current physiological status score, α, β, and γ are weight coefficients, which are allocated according to the importance of each factor to personalized recommendation, and α+β+γ=1.

9. The method for aiding sleep with massage audio according to claim 8, characterized in that: In step S3, user data preprocessing includes at least one of clearing abnormal data, removing duplicate data, integrating data from multiple data sources into an integrated data set, and data weight processing; and / or, In step S5, real-time physiological data of the user is collected by a non-contact sensor; and / or, In step S6, the real-time physiological data, massage data and audio data of the sleep cycle are sent to the cloud server, and the cloud server sends a modification instruction to the smart sleep-aid pillow, and the smart sleep-aid pillow adjusts the massage audio mode, thereby adjusting the massage and / or audio settings during the sleep cycle.

10. An intelligent sleeping-aiding pillow with massage audio function, characterized in that: A massage audio sleep-aiding method according to any one of claims 1 to 9 is adopted, wherein the smart sleep-aiding pillow comprises: a smart sleep-aiding pillow body (1), including a sleep-aiding pillow core base (11), a sleep-aiding pillow cover (12), a fingertip airbag (13), a sleep-aiding audio module unit (14) and a signal acquisition unit; Air pressure source; A control unit receives the signal sent by the signal acquisition unit and controls the air pressure source and the sleep-aiding audio module unit (14); The integrated air-electric connection unit (3) is connected to the air pressure source and the fingertip airbag (13), and is connected to the control unit and the sleep-aiding audio module unit (14).

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